Individual differences in cue-weighting in sentence comprehension: An evaluation using Approximate Bayesian Computation
Oberseminar "General & Theoretical Linguistics" by Shravan Vasishth
Time & place: Monday, February 22nd, 11.00 am - 12.30 pm, Zoom
Zoom link: https://zoom.us/j/96320858663
Meeting ID: 963 2085 8663
Speaker: Shravan Vasishth, University of Potsdam
Title: Individual differences in cue-weighting in sentence comprehension: An evaluation using Approximate Bayesian Computation
Abstract: Cue-based retrieval theories of sentence processing assume that syntactic dependencies are resolved through a content-addressable search process. An important recent claim is that in certain dependency types, the retrieval cues are weighted such that one cue dominates. This cue-weighting proposal aims to explain the observed average behavior. We show that there is systematic individual-level variation in cue weighting. Using the Lewis and Vasishth cue-based retrieval model, we estimated individual-level parameters for processing speed and cue weighting using data from 13 published reading studies; hierarchical Approximate Bayesian Computation (ABC) with Gibbs sampling was used to estimate the parameters. The modeling reveals a nuanced picture about cue-weighting: we find support for the idea that some participants weight cues, but not all do; and only fast readers tend to have the predicted cue weighting, suggesting that reading proficiency might be associated with cue weighting. A broader achievement of the work is to demonstrate how individual differences can be investigated in computational models of sentence processing using hierarchical ABC.
More information about this and past talks in the Oberseminar can be found here: https://uni-tuebingen.de/de/133999.